acr2csm

class diffsptk.AutocorrelationToCompositeSinusoidalModelCoefficients(csm_order)

See this page for details.

Parameters:

csm_orderint >= 0

Order of CSM coefficients, \(M\).

References

[1]

S. Sagayama et al., “Duality theory of composite sinusoidal modeling and linear prediction,” Proceedings of ICASSP, pp. 1261-1264, 1986.

forward(r)

Convert autocorrelation to CSM coefficients.

Parameters:

rTensor [shape=(…, M+1)]

Autocorrelation.

Returns:

outTensor [shape=(…, M+1)]

Composite sinusoidal model coefficients.

Examples

>>> x = diffsptk.nrand(4)
>>> x
tensor([ 0.0165, -2.3693,  0.1375, -0.2262,  1.3307])
>>> acorr = diffsptk.Autocorrelation(5, 3)
>>> acr2csm = diffsptk.AutocorrelationToCompositeSinusoidalModelCoefficients(3)
>>> c = acr2csm(acorr(x))
>>> c
tensor([0.9028, 2.5877, 3.8392, 3.6153])

diffsptk.functional.acr2csm(r)

Convert autocorrelation to CSM coefficients.

Parameters:

rTensor [shape=(…, M+1)]

Autocorrelation.

Returns:

outTensor [shape=(…, M+1)]

CSM coefficients.

See also

acorr csm2acr